融合语义分析和脱钩理论的公众空气污染风险感知偏差研究

熊欣; 邱建宏; 赵锐; 任昕芸

doi:10.13205/j.hjgc.202602019

融合语义分析和脱钩理论的公众空气污染风险感知偏差研究

doi: 10.13205/j.hjgc.202602019

西南交通大学环境科学与工程学院, 成都 611756

基金项目:

国家自然科学基金项目“基于区域重点建设项目环境影响的社会风险演化机制与评估体系研究”（41571520）；四川省环境类教学指导委员会重点项目“面向双碳战略，新质生产力驱动的环境工程教育教学实践与研究”（CHJZW202403）；四川省教学改革项目“以双碳为引领，新质生产力赋能环境工程教育教学的探索与实践”（SCJX2024334）

详细信息

作者简介:
熊欣，讲师，主要研究方向为环境系统模拟、环境行为分析。xiongxin@swjtu.edu.cn

通讯作者:
赵锐，教授，主要研究方向为环境系统工程。ruizhao@swjtu.edu.cn

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出版历程
- 收稿日期: 2025-03-18
- 网络出版日期: 2026-04-11
- 刊出日期: 2026-02-01

Public perception bias of air pollution risk based on semantic analysis and decoupling theory

School of Environmental Science and Engineering, Southwest Jiaotong University, Chengdu 611756, China

摘要

摘要: 空气污染是全球面临的严重环境健康风险之一。受个体感官差异（如视觉）和周边环境（如能见度）的影响，公众通常难以准确评判空气污染的风险程度。通过文本语义分析方法评价公众对空气污染的主观风险感知水平，并创新性地借鉴脱钩理论构建风险感知偏差指数，量化主观风险感知与真实风险水平间的差异，并以成都市为例进行实证研究。结果表明：1）在空气污染预警信息发布较多的年份，以及空气污染较为严重的秋冬季节，公众发布空气污染相关文本较多，对空气污染的关注度较高。2）公众空气污染主观风险感知评分存在季节性差异，在秋冬和春夏季节均值分别为-1.5和4.9，表明秋冬季节公众在主观上认为空气污染带来的健康风险更大。3）公众空气污染主观风险感知与真实风险水平存在不一致性，高估和低估风险的现象同时存在，在秋冬季节，由于以颗粒物（如PM_2.5和PM₁₀）为主的污染物对个体感官的影响更加直观和强烈，公众高估风险的比例（26.9%）明显高于春夏季（15.1%）。4）管理部门一方面需根据不同季节的污染特征制定差异化的污染物管控策略，另一方面需通过信息发布和宣传教育等手段，加强公众对空气污染风险的正确认知，避免因信息不对称引发社会舆情，同时也可帮助公众正确防控空气污染带来的健康风险。
- 空气污染 /
- 风险感知 /
- 风险感知偏差 /
- 文本语义分析 /
- 脱钩弹性指数
Abstract: Air pollution poses serious challenges to both the environment and human health. Influenced by individual sensory characteristics （such as visual sense） and environmental context （such as visibility）， the public often struggles to accurately assess air pollution risk levels. By integrating textual semantic analysis with decoupling theory， this study proposed a novel Public Air Pollution Risk Perception Bias Index to quantify the gap between subjective risk perception and actual risk levels， taking Chengdu as a case study for empirical analysis. Results showed that： 1） In the years with more frequent air pollution warnings and the autumn and winter seasons with more severe air pollution， the number of air pollution-related texts peaked， indicating heightened public concern during these periods. 2） There are seasonal differences in the public’s subjective risk perception scores of air pollution， with average values of -1.5 in autumn and winter， and 4.9 in spring and summer. This indicates that the public subjectively perceives air pollution to pose greater health risks during autumn and winter seasons. 3） A discrepancy existed between the public’s subjective risk perception and the actual risk levels， with both overestimation and underestimation occurring. In autumn and winter， due to the more direct and intense sensory impact of pollutants， which mainly consisted of particulate matter such as PM_2.5and PM₁₀， the proportion of overestimating the risk （26.9%） was significantly higher than that in spring and summer （15.1%）. 4） On the one hand， regulatory authorities should develop differentiated pollutant control strategies based on the seasonal characteristics of pollution； On the other hand， they should strengthen public awareness and accurate understanding of air pollution risks through information dissemination and public education.
- air pollution /
- risk perception /
- risk perception bias /
- text semantic analysis /
- decoupling elasticity index

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参考文献(36)

[1]	SING T，WANG W，ZHAN C. Tracking industry pollution sources and health risks in China［J］. Scientific Reports，2023，13（1）:22232.
[2]	TIAN Y，LIU X，HUO R，et al. Organic compound source profiles of PM_2.5 from traffic emissions，coal combustion，industrial processes and dust［J］. Chemosphere，2021，278:130429.
[3]	YOO E，PU Q，EUM Y，et al. The impact of individual mobility on long-term exposure to ambient PM_2.5:assessing effect modification by travel patterns and spatial variability of PM_2.5［J］. International Journal of Environmental Research and Public Health，2021，18（4）:2194.
[4]	DI CLEMENTE R，STRANO E，BATTY M. Urbanization and economic complexity［J］. Scientific Reports，2021，11（1）:3952.
[5]	SALMAN M Y，HASAR H. Review on environmental aspects in smart city concept:water，waste，air pollution and transportation smart applications using IoT techniques［J］. Sustainable Cities and Society，2023，94:104567.
[6]	Ministry of Ecology and Environment，People’s Republic of China. Report on the state of the ecology and environment in China 2023［R］. Beijing，Ministry of Ecology and Environment，2024:3-4. 中华人民共和国生态环境部. 2023年中国生态环境状况公报［R］. 北京:中华人民共和国生态环境部，2024:3-4.
[7]	RENTSCHLER J，LEONOVA N. Global air pollution exposure and poverty［J］. Nature Communications，2023，14（1）:4432.
[8]	CAO Z，ZHOU J，LI M，et al. Urbanites’ mental health undermined by air pollution［J］. Nature Sustainability，2023，6（5）:470-478.
[9]	SLOVIC P. Risk perception［M］// TRAVIS C C. Carcinogen Risk Assessment. New York:Springer，1988:171-181.
[10]	ZHAO R，LIU J，Z Y Y，et al. Risk perception towards atmospheric environment based on text datamining of public opinions［J］. Environmental Engineering，2022，40（4）:209-216. 赵锐，刘婕，周宇羽，等. 基于环境舆情文本挖掘的大气环境风险感知评价［J］. 环境工程，2022，40（4）:209-216.
[11]	LU B F，LIU B B. Analysis of public risk perception on haze and suggestions for improving risk communication［J］. Sichuan Environment，2022，41（6）:93-99. 陆卜梵，刘蓓蓓. 公众对霾的风险感知研究及风险交流改善建议［J］. 四川环境，2022，41（6）:93-99.
[12]	HUANG J，YANG J. Beyond under the dome:an environmental documentary amplified public risk perception about air pollution in China［J］. Journal of Risk Research，2020，23（2）:227-241.
[13]	PU S，SHAO Z，FANG M，et al. Spatial distribution of the public’s risk perception for air pollution:a nationwide study in China［J］. Science of the Total Environment，2019，655:454-462.
[14]	HUANG L，RAO C，van der KUIJP T J，et al. A comparison of individual exposure，perception，and acceptable levels of PM_2.5 with air pollution policy objectives in China［J］. Environmental Research，2017，157:78-86.
[15]	LI W，YANG G，LI X. Correlation between PM_2.5 pollution and its public concern in China:evidence from Baidu Index［J］. Journal of Cleaner Production，2021，293:126091.
[16]	LONG Y，ZHENG D，WEI Y，et al. Impact of risk perception on intrapersonal heterogeneity in decision-making processes by air pollution context:a latent variable and latent class regret-utility approach［J］. Journal of Cleaner Production，2023，428:139305.
[17]	SCAMMELL M K. Qualitative environmental health research:an analysis of the literature，1991—2008［J］. Environmental Health Perspectives，2010，118（8）:1146-1154.
[18]	NOËL C，van LANDSCHOOT L，VANROELEN C，et al. The public’s perceptions of air pollution. What’s in a name？［J］. Environmental Health Insights，2022，16:211-235.
[19]	DONG D，XU X，XU W，et al. The relationship between the actual level of air pollution and residents’ concern about air pollution:evidence from Shanghai，China［J］. International Journal of Environmental Research and Public Health，2019，16（23）:4784.
[20]	YE B，KRISHNAN P，JIA S. Public concern about air pollution and related health outcomes on social media in China:an analysis of data from Sina Weibo（Chinese Twitter）and air monitoring stations［J］. International Journal of Environmental Research and Public Health，2022，19（23）:16115.
[21]	LI M，CH'NG E，CHONG A，et al. The new eye of smart city:novel citizen sentiment analysis in Twitter［C］// International Conference on Audio，IEEE. Shanghai:Language and Image Processing，2016:557-562.
[22]	BAO Q，ZHANG X，WU X，et al. Research on public environmental perception of emotion，taking haze as an example［J］. International Journal of Environmental Research and Public Health，2021，18:2115.
[23]	MADJAR A，GJORSHOSKA I，PRODANOVA J，et al. Western Balkan societies’ awareness of air pollution. Estimations using natural language processing techniques［J］. Ecological Informatics，2023，75:102097.
[24]	YE J T，WANG Y. Research on environmental risk perception bias of megacities:findings based on survey data of urban communities in Shanghai［J］. Urban Problems，2022（3）:76-83. 叶锦涛，王阳. 特大城市居民环境风险感知偏差研究:基于上海都市社区调查数据的发现［J］. 城市问题，2022（3）:76-83.
[25]	LI Q，XIA M，GUO X，et al. Spatial characteristics and influencing factors of risk perception of haze in China:the case study of publishing online comments about haze news on Sina［J］. Science of the Total Environment，2021，785:147236.
[26]	ZHANG S，WEI Z，WANG Y，et al. Sentiment analysis of Chinese micro-blog text based on extended sentiment dictionary［J］. Future Generation Computer Systems，2018，81:395-403.
[27]	YADOLLAHI A，SHAHRAKI A G，ZAIANE O R. Current state of text sentiment analysis from opinion to emotion mining［J］. ACM Computing Surveys（CSUR），2017，50（2）:1-33.
[28]	YANG J，ZHOU Q，LIU X，et al. Biased perception misguided by affect:how does emotional experience lead to incorrect judgments about environmental quality？［J］. Global Environmental Change，2018，53:104-113.
[29]	TAPIO P. Towards a theory of decoupling:degrees of decoupling in the EU and the case of road traffic in Finland between 1970 and 2001［J］. Transport Policy，2005，12（2）:37-151.
[30]	Chengdu Municipal Ecology and Environment Bureau Prevention and control of air pollution［EB/OL］.（2024-01-14）［2024-06-21］. https://sthj.chengdu.gov.cn/cdhbj/c169812/zwgk_dqwr.shtml. 成都市生态环境局. 大气污染防治［EB/OL］.（2024-01-14）［2024-06-21］. https://sthj.chengdu.gov.cn/cdhbj/c169812/zwgk_dqwr.shtml.
[31]	ZHANG Y，WU W，LI Y，et al. An investigation of PM_2.5 concentration changes in Mid-Eastern China before and after COVID-19 outbreak［J］. Environment International，2023（175）:107941.
[32]	WU W，WANG W，ZHANG L，et al. Does the public haze pollution concern expressed on online platforms promoted pollution control？ Evidence from Chinese online platforms［J］. Journal of Cleaner Production，2021，318:128477.
[33]	MOUSAVINEZHAD S，CHOI Y，POUYAEI A，et al. A comprehensive investigation of surface ozone pollution in China，2015—2019:separating the contributions from meteorology and precursor emissions［J］. Atmospheric Research，2021，257:105599.
[34]	WANG J，YANG Y，ZHANG Y，et al. Influence of meteorological conditions on explosive increase in O₃ concentration in troposphere［J］. Science of the Total Environment，2019，652:1228-1241.
[35]	FENG Y，ZHAO L X，LIU B Y，et al. Current situation and suggestion for air pollution emission control of steel industry in Guanxi［J］. Environmental Engineering，2024，42（6）:63-70. 冯媛，赵侣璇，刘冰燕，等. 广西钢铁行业大气污染治理现状及控制对策建议［J］. 环境工程，2024，42（6）:63-70.
[36]	Chengdu Bureau of Statistics. Chengdu statistical yearbook 2024［M］. Beijing:China Statistics Press，2024. 成都市统计局. 成都统计年鉴2024［M］. 北京:中国统计出版社，2024.